{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "textile-serial",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "noble-hungary",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "blank = np.zeros(shape=(600, 800, 3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "victorian-modeling",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x26a32dd3388>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(blank)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "steady-computer",
   "metadata": {},
   "outputs": [],
   "source": [
    "boxed = cv2.rectangle(blank, (0, 0), (400, 400), (0, 255, 0), thickness=-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "neutral-roller",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x26a36546cc8>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(blank)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "outdoor-poster",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x26a3658c4c8>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(boxed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "exciting-spotlight",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "array() missing required argument 'object' (pos 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-7-55e5f6211762>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mwhite\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: array() missing required argument 'object' (pos 1)"
     ]
    }
   ],
   "source": [
    "white = np.array()"
   ]
  }
 ],
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